E-LIB Suche - Ergebnisse für: Costabal, Francisco Sahli

1

Dassault Systèmes' Living Heart Project:

, In: Modelling Congenital Heart Disease,

Levine, Steven ; Battisti, Tom ; Butz, Björn... - p. 245-259 , 2022

2

How viscous is the beating heart? Insights from a computati..:

Tikenoğulları, Oğuz Ziya ; Costabal, Francisco Sahli ; Yao, Jiang..
Computational Mechanics. 70 (2022) 3 - p. 565-579 , 2022

Link: https://doi.org/10.1007/..

3

Learning Atrial Fiber Orientations and Conductivity Tensors..:

, In: Functional Imaging and Modeling of the Heart; Lecture Notes in Computer Science,

Grandits, Thomas ; Pezzuto, Simone ; Costabal, Francisco Sahli... - p. 650-658 , 2021

Link: https://doi.org/10.1007/..

4

COVID-19 dynamics across the US: A deep learning study of h..:

Bhouri, Mohamed Aziz ; Costabal, Francisco Sahli ; Wang, Hanwen...
Computer Methods in Applied Mechanics and Engineering. 382 (2021) - p. 113891 , 2021

Link: https://doi.org/10.1016/..

5

Physics-informed neural networks for parameter estimation i..:

Garay, Jeremías ; Dunstan, Jocelyn ; Uribe, Sergio.
Computers in Biology and Medicine. 178 (2024) - p. 108706 , 2024

Link: https://doi.org/10.1016/..

6

Generative hyperelasticity with physics-informed probabilis..:

Taç, Vahidullah ; Rausch, Manuel K. ; Bilionis, Ilias..
Engineering with Computers. , 2024

Link: https://doi.org/10.1007/..

7

Machine learning modeling of lung mechanics: Assessing the ..:

Barahona, José ; Sahli Costabal, Francisco ; Hurtado, Daniel E.
Computer Methods and Programs in Biomedicine. 243 (2024) - p. 107888 , 2024

Link: https://doi.org/10.1016/..

8

Δ-PINNs: Physics-informed neural networks on complex geomet..:

Sahli Costabal, Francisco ; Pezzuto, Simone ; Perdikaris, Paris
Engineering Applications of Artificial Intelligence. 127 (2024) - p. 107324 , 2024

Link: https://doi.org/10.1016/..

9

The Fibrotic Kernel Signature: Simulation-Free Prediction o..:

, In: Functional Imaging and Modeling of the Heart; Lecture Notes in Computer Science,

Sahli Costabal, Francisco ; Banduc, Tomás ; Gander, Lia. - p. 87-96 , 2023

Link: https://doi.org/10.1007/..

10

Data-driven anisotropic finite viscoelasticity using neural..:

Taç, Vahidullah ; Rausch, Manuel K. ; Sahli Costabal, Francisco.
Computer Methods in Applied Mechanics and Engineering. 411 (2023) - p. 116046 , 2023

Link: https://doi.org/10.1016/..

11

WarpPINN: Cine-MR image registration with physics-informed ..:

Arratia López, Pablo ; Mella, Hernán ; Uribe, Sergio..
Medical Image Analysis. 89 (2023) - p. 102925 , 2023

Link: https://doi.org/10.1016/..

12

On the Accuracy of Eikonal Approximations in Cardiac Electr..:

, In: Functional Imaging and Modeling of the Heart; Lecture Notes in Computer Science,

Gander, Lia ; Krause, Rolf ; Weiser, Martin.. - p. 137-146 , 2023

Link: https://doi.org/10.1007/..

13

Fast Characterization of Inducible Regions of Atrial Fibril..:

Gander, Lia ; Pezzuto, Simone ; Gharaviri, Ali...
Frontiers in Physiology. 13 (2022) - p. , 2022

Link: https://doi.org/10.3389/..

14

Data-driven tissue mechanics with polyconvex neural ordinar..:

Tac, Vahidullah ; Sahli Costabal, Francisco ; Tepole, Adrian B.
Computer Methods in Applied Mechanics and Engineering. 398 (2022) - p. 115248 , 2022

Link: https://doi.org/10.1016/..

15

Physics-informed neural networks to learn cardiac fiber ori..:

Ruiz Herrera, Carlos ; Grandits, Thomas ; Plank, Gernot...
Engineering with Computers. 38 (2022) 5 - p. 3957-3973 , 2022

Link: https://doi.org/10.1007/..